Pharmaceuticals giant AstraZeneca has closed on a deal with US-based biotech AbSci Corporation to develop an antibody therapy for an undisclosed cancer using Absci’s AI technology.

The deal, signed yesterday (3 November), is worth up to $247m, according to the Financial Times. It is said to include milestone payments, royalty sharing and an upfront sum.

Absci is a pioneer in healthcare-focused generative artificial intelligence (AI), using its lab in New York to compare millions of protein samples that are then fed into its model with the aim of discovering novel antibodies. This kind of technology has been particularly promising in the rare disease space, where the cost-cutting and time-saving benefits of AI have allowed drugs to be trialled that would otherwise not have been cost-effective.

The company has a focus on oncology drugs, having signed a partnership agreement earlier this year with bioinformatics firm M2GEN to expand its library of antibodies and proteins.

AstraZeneca, alongside other pharma giants, is increasingly interested in cell therapies including antibody therapies as cancer treatments. While unlikely to replace current chemotherapy and radiotherapy in the near future due to scalability and cost concerns, the benefits of these drugs are potentially huge. By specialising treatments for particular patient populations or forms of cancer, they can offer significantly higher remission rates than traditional remedies.

Oncology remains the most heavily invested discipline for AI-related deals, with over $250bn invested in 2023 alone, according to analytics from GlobalData, Medical Device Network’s parent company. Overall, however, AI deals have decreased in value across the board since 2019. This may in part be due to market maturation. As the market grows, the total level of investment comes closer to saturation, meaning lower levels are needed in the future.

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By GlobalData

However, concerns over the efficacy of AI in developing drugs may also be a contributing factor. Endpoints reported earlier this year that the first wave of AI-designed drugs have all failed at either the clinical or preclinical stage. This does not suggest that AI will not be useful in drug development, but has quashed some of the hype regarding the furthest possibilities of its use.

Our signals coverage is powered by GlobalData’s Thematic Engine, which tags millions of data items across six alternative datasets — patents, jobs, deals, company filings, social media mentions and news — to themes, sectors and companies. These signals enhance our predictive capabilities, helping us to identify the most disruptive threats across each of the sectors we cover and the companies best placed to succeed.